基于随机波动模型的石油上市公司股价波动性分析

发布时间：2018-01-02 00:13

本文关键词：基于随机波动模型的石油上市公司股价波动性分析　出处：《浙江工业大学》2014年硕士论文　论文类型：学位论文

【摘要】：石油由于其固有的特性及其巨大的效应,成为一大研究热点。地球上石油的储量是固定的,但生活中我们根本无法离开它,久而久之,总有一天会“油尽灯枯”。而众多的因素会导致国际油价频繁波动,对于中国这个人多资源缺乏的国家而言影响很大,股票市场就是其中之一。相比发达国家,我国股票市场起步较晚,对外界的刺激反映很敏感,股价偏离正常的定价机制,这对于经济健康、稳定地发展很不利。因此,股价波动性的研究就显得很有必要,股价波动性一直以来都是学者们研究的热点。但现有的研究都只是单独的研究其中之一,而没有把两者放在一起研究过。因此,本文的研究目标就是研究我国与石油相关的上市公司股价的波动性,并用得到的结果对未来的股价波动进行一定的预测。本文采用随机波动模型和广义自回归条件异方差模型来研究我国与石油相关的上市公司股价的波动性,选取一定期间的数据为样本,分成采矿业与制造业两块来进行分析。经过数据的分析,发现随机波动模型相比广义自回归条件异方差模型能够较好地捕捉到波动聚集、尖峰厚尾的特征,同时,通过使用R软件,能够很好地进行模拟,并得到一系列模拟数据,还对样本外的股价进行了预测,将复杂的经济动态直观地展现在我们面前。最后,根据研究结果,从石油和股市两个层面提出了适当的建议。
[Abstract]:Because of its inherent characteristics and its enormous effects, oil has become a hot research topic. The oil reserves on the earth are fixed, but we can not leave it in life. One day, "oil will run out". And many factors will lead to frequent fluctuations in international oil prices, for China, a country with a lack of human resources, the stock market is one of them. Compared with developed countries, the stock market is one of them. The stock market of our country starts relatively late, is very sensitive to the outside stimulus, the stock price deviates from the normal pricing mechanism, this is very unfavorable to the economic health, the stable development. It is necessary to study the volatility of stock price, which has always been the focus of scholars, but the existing research is only one of the separate studies. Therefore, the research goal of this paper is to study the volatility of stock price of oil related listed companies in China. In this paper, stochastic volatility model and generalized autoregressive conditional heteroscedasticity model are used to study the volatility of oil related listed companies in China. Selected a certain period of data as a sample, divided into two blocks of mining and manufacturing to analyze. After the analysis of the data. It is found that compared with the generalized autoregressive conditional heteroscedasticity model, the stochastic volatility model can capture the characteristics of wave aggregation and peak thick tail better than the generalized autoregressive conditional heteroscedasticity model. At the same time, by using R software, it can be well simulated. And get a series of simulation data, but also forecast the stock price outside the sample, and show the complex economic dynamics in front of us intuitively. Finally, according to the research results. From the oil and stock market two levels of appropriate recommendations.
【学位授予单位】：浙江工业大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：F426.22;F832.51

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